Staff Software Engineer, Enterprise AI (Intelligence Platform)

About the Role

As a Staff Full-Stack Software Engineer specializing in AI, you will personally design and build the AI agent capabilities and product experiences for an internal enterprise intelligence platform. This includes the retrieval, orchestration, and reasoning layer that sits on top of a semantic data layer built and maintained by a partner data engineering team. You’ll turn these capabilities into search, chat, and workflow experiences that help leaders find information and make decisions faster. This is a hands-on, coding-majority role where you'll build agents, prompts, tool integrations, and the full-stack product surface.

You’ll work directly with product owners, system leads, and domain experts across HR, Finance, IT, Legal, and Workplace to understand workflows, while collaborating closely with the data engineering team that owns data ingestion, the semantic layer, and data modeling.

The role reports to the Manager of Enterprise Systems Engineering.

Responsibilities

• Build and maintain an orchestrator + specialist-agent architecture (retrieval, tool use, structured outputs, multi-step reasoning) on top of a semantic data layer.
• Design and implement retrieval and grounding for RAG/semantic search use cases: embeddings, reranking, citation of evidence, and hallucination reduction.
• Integrate agents with internal and external tools/APIs (function/tool calling) to execute actions.
• Build the full-stack application layer, APIs, and UI that exposes AI-powered search, chat, and workflow experiences.
• Instrument AI features with observability for quality, latency, token usage, and cost to drive iteration and tuning.
• Iterate on prompts and model choices with fallback behavior for low-confidence or failed steps.
• Apply solid engineering fundamentals: source control, code review, automated testing (unit, integration, functional), CI/CD, and on-call rotation.

Required Qualifications

• Bachelor's degree in Computer Engineering, Computer Science, Information Systems, or related field (or equivalent professional experience delivering enterprise technology solutions).
• 8+ years of professional experience in full-stack software development.
• Practical, end-to-end experience building RAG or agentic systems (retrieval, tool-calling, structured outputs, multi-step reasoning, verification/evaluation loops).
• Experience designing and running evaluation approaches for nondeterministic systems (curated datasets, automated metrics, human review, production feedback).
• Experience establishing AI observability (quality, safety, reliability, latency, token usage, cost).
• Working understanding of AI security and responsible-use risks (prompt injection, tool abuse, data leakage, access control, model limitations).
• Deep hands-on programming experience in Node, TypeScript, and React.
• Experience with modern frameworks such as Next.js and NestJS.
• Experience building RESTful and GraphQL APIs, working with relational (PostgreSQL, MySQL) and non-relational (Redis) databases.
• Experience with cloud infrastructure and deployment: AWS, Docker, Kubernetes, CI/CD pipelines.
• Familiarity with software engineering best practices: automated testing, code review, monitoring/observability, security, and performance.

Desired Qualifications

• Deep practical knowledge of retrieval-augmented generation and semantic search (embedding and reranking models, retrieval design, grounding, citations, evaluation).
• Experience with agent platforms (LangGraph, AutoGen, CrewAI), vector databases, and multi-agent orchestration patterns.
• Working familiarity with Python and lakehouse/data-catalog concepts (Databricks, Unity Catalog).
• Experience shipping an internal AI product from scratch in a small, fast-moving team environment with an iterative MVP delivery approach.